Premium
Analytical shape computation of macromolecules: I. molecular area and volume through alpha shape
Author(s) -
Liang Jie,
Edelsbrunner Herbert,
Fu Ping,
Sudhakar Pamidighantam V.,
Subramaniam Shankar
Publication year - 1998
Publication title -
proteins: structure, function, and bioinformatics
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.699
H-Index - 191
eISSN - 1097-0134
pISSN - 0887-3585
DOI - 10.1002/(sici)1097-0134(19981001)33:1<1::aid-prot1>3.0.co;2-o
Subject(s) - computation , voronoi diagram , macromolecule , discretization , duality (order theory) , alpha (finance) , metric (unit) , computer science , algorithm , statistical physics , mathematics , physics , geometry , chemistry , pure mathematics , mathematical analysis , statistics , operations management , economics , biochemistry , construct validity , psychometrics
The size and shape of macromolecules such as proteins and nucleic acids play an important role in their functions. Prior efforts to quantify these properties have been based on various discretization or tessellation procedures involving analytical or numerical computations. In this article, we present an analytically exact method for computing the metric properties of macromolecules based on the alpha shape theory. This method uses the duality between alpha complex and the weighted Voronoi decomposition of a molecule. We describe the intuitive ideas and concepts behind the alpha shape theory and the algorithm for computing areas and volumes of macromolecules. We apply our method to compute areas and volumes of a number of protein systems. We also discuss several difficulties commonly encountered in molecular shape computations and outline methods to overcome these problems. Proteins 33:1–17, 1998. © 1998 Wiley‐Liss, Inc.